84
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# Checking if we have argparse (which is default in 2.7 so this is
# probably a useless check since we already check if Python is 2.7) try :
import argparse except :
print "Argparse Not Available?! You sure this is Python 2.7?"
raise SystemExit
# The WWZ Class Begins
class WWZ(object) :
"""The Main class object.
This object class does not get any arguments.
Available methods are:
readfile() roundtau() maketau() makefreq() matrix_inv() wwt()
writefile() writegnu()
Arguments :
fileName : the input filename, should be the lightcurve.
outputfileName : the output filename.
flo : the low frequency value. Float.
fhi : the high frequency value. Float.
df : the frequency step. Float.
dcon : the C Window constant. Float.
timedivisions : the The Divisions value, choose 50.0 if not sure, that is the default used by Templeton.
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max_periods : set True if you want the second output file.
It outputs the tau's with maximum period values for easier estimation.
gnuplot_compatible : splits tau values by a blank line if set True, so that pm3d of gnuplot easily maps the plot.
"""
def __init__(self) :
"""Initializing the object"""
def readfile(self, fileName) : """Read the input file.
The argument is the file pointer, not the filename as a string.
The values in file should be delimited with spaces or tabs.
Ignores lines starting with # and %, as if they're comment lines.
Returns two arrays :
Time value, read from the first column of input file.
Magnitude value, read from the second column of input file.
"""
time = []
magnitude = []
for line in fileName :
# Check if it's a comment line
if line.strip()[0] != "%" and line.strip()[0] != "#" : line_time = float(line.split()[0])
line_mag = float(line.split()[1]) time.append(line_time)
magnitude.append(line_mag)
fileName.close()
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# Just a routine check for parameter number equality # This should be cleaned up a bit
if len(time) != len(magnitude) :
print "Number of Time and Magnitude input do not match. \ Please check the input file."
raise SystemExit
# Return two arrays return time, magnitude
def roundtau(self, darg) :
"""Rounds the tau's. from G. Foster's Code.
This is actually called by the maketau method.
The input is dtspan/timedivisions,
where dtspan is the entire timespan of the lightcurve.
so dtspan = time[-1] - time[0]
Returns the round value.
"""
dex = math.log(darg, 10) nex = int(dex)
darg = darg / math.pow(10, nex)
if darg >= 5 : darg = 5.0 elif darg >= 2 : darg = 2.0 else :
darg = 1.0
darg = darg * math.pow(10, nex) return darg
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def matrix_inv(self, inputMatrix) : """The Matrix Inversion Method.
Arguments are :
inputMatrix : the input matrix_inv
Returns the inverted matrix.
"""
# Lines 202 - 252 Fortran
ndim = 2
dsol = numpy.zeros(shape=(3, 3))
for i in range(0, 3) : for j in range(0, 3) : dsol[i][j] = 0.0 dsol[i][i] = 1.0
for i in range(0, 3) :
if inputMatrix[i][i] == 0.0 : if i == ndim :
return
for j in range(0, 3) :
if inputMatrix[j][i] != 0.0 : for k in range(0, 3) :
inputMatrix[i][k] = inputMatrix[i][k] + \ inputMatrix[j][k]
dsol[i][j] = dsol[i][j] + dsol[j][k]
dfac = inputMatrix[i][i]
for j in range(0, 3) :
inputMatrix[i][j] = inputMatrix[i][j] / dfac dsol[i][j] = dsol[i][j] / dfac
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for j in range(0, 3) : if j != i :
dfac = inputMatrix[j][i]
for k in range(0, 3) :
inputMatrix[j][k] = inputMatrix[j][k] - \ (inputMatrix[i][k] * dfac) dsol[j][k] = dsol[j][k] - (dsol[i][k] * dfac)
# The unnecessery loop #for i in range(0, 3) : #for j in range(0, 3) :
#self.dmat[i][j] = dsol[i][j]
return dsol
def maketau(self, time, timedivisions):
"""The maketau method.
Arguments are :
time = The array of time values
timedivisions = The value of timedivisions to create tau values
Returns an array of calculated tau values.
"""
# The Maketau section # Lines 90 - 122 Fortran
dtauhi = time[-1]
dtaulo = time[0]
# the java translation uses 1 for dtaulo, # but that should be a bug.
dtspan = dtauhi - dtaulo
dtstep = self.roundtau(dtspan / timedivisions)
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dtaulo = dtstep * int(dtaulo / dtstep)
dtauhi = dtstep * int((dtauhi / dtstep) + 0.5)
tau = []
dtau = dtaulo
while dtau <= dtauhi : tau.append(dtau) dtau = dtau + dtstep return tau
### End of Maketau
def makefreq(self, flo, fhi, df):
"""The Makefreq section.
Arguments are :
flo = Low Frequency fhi = High Frequency df = Frequency Step """
# Lines 149 - 181 Fortran # Lines 356 - 370 Java freq = []
freq.append(flo)
nfreq = int((fhi - flo) / df) + 1
# These lines seem skeptical!
for i in range(1,nfreq+1) :
freq.append(flo + ((i - 1) * df))
return freq
### End of Makefreq
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def wwt(self, time, magnitude, flo, fhi, df, dcon, timedivisions) : """The WWZ Algorithm
Arguments are :
time = The time values as an array
magnitude = The magnitude values as an array flo = The Low Frequency
fhi = The High Frequency df = The Frequency Step
dcon = The C constant of WWZ Window timedivisions = The TAU steps
Returns a NumPy Array """
dave = numpy.mean(magnitude) dvar = numpy.var(magnitude)
freq = self.makefreq(flo, fhi, df) nfreq = len(freq)
dmat = numpy.zeros(shape=(3,3))
### End of Initializing
tau = self.maketau(time, timedivisions) ntau = len(tau)
### WWT Stars Here
dvec = [0,0,0] # length is 3 dcoef = [0,0,0] # length is 3
itau = 0 ifreq = 0 idat = 0
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domega = 0.0 dweight2 = 0.0 dz = 0.0 dweight = 0.0
dcc = 0.0 dcw = 0.0 dss = 0.0 dsw = 0.0 dxw = 0.0 dvarw = 0.0
dtau = 0.0
dpower = 0.0 dpowz = 0.0 damp = 0.0 dneff = 0.0 davew = 0.0
dfre = 0.0
n1 = 0 n2 = 0
dmz = 0.0 dmzfre = 0.0 dmzamp = 0.0 dmcon = 0.0 dmneff = 0.0
twopi = 2.0 * math.pi
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ndim = 2
itau1 = 0 # --> 1 or 0 ??
itau2 = ntau # --> ???
ifreq1 = 1 ifreq2 = nfreq nstart = 1
# Creating output arrays
output = numpy.empty((ntau*(nfreq-1), 6)) numdat=len(time)
index = 0
# Use for itau in range(itau1,itau2) for parallel for itau in range(0, itau2) :
nstart = 1 dtau = tau[itau]
dmfre = 0.0 dmamp = 0.0 dmcon = 0.0 dmneff = 0.0
dmz = -1.0 # less than the smallest WWZ
for ifreq in range(ifreq1, ifreq2) : dfre = freq[ifreq]
domega = dfre * twopi
for i in range(0, ndim + 1) : dvec[i] = 0.0
for j in range(0, ndim + 1) : dmat[i][j] = 0.0
dweight2 = 0.0
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for idat in range(nstart, numdat) :
dz = domega * (time[idat] - dtau)
dweight = math.exp(-1.0 * dcon * dz * dz)
if (dweight > 10**(-9)) : dcc = math.cos(dz) dcw = dweight * dcc dss = math.sin(dz) dsw = dweight * dss
dmat[0][0] = dmat[0][0] + dweight dweight2 = dweight2 + (dweight**2) dmat[0][1] = dmat[0][1] + dcw dmat[0][2] = dmat[0][2] + dsw
dmat[1][1] = dmat[1][1] + (dcw * dcc) dmat[1][2] = dmat[1][2] + (dcw * dss) dmat[2][2] = dmat[2][2] + (dsw * dss)
dxw = dweight * magnitude[idat]
dvec[0] = dvec[0] + dxw
dvarw = dvarw + (dxw * magnitude[idat]) dvec[1] = dvec[1] + (dcw * magnitude[idat]) dvec[2] = dvec[2] + (dsw * magnitude[idat])
elif dz > 0.0 : break else :
nstart = idat + 1
dpower = 0.0 damp = 0.0
for n1 in range(0, ndim + 1) : dcoef[n1] = 0.0
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if (dweight2 > 0.0) :
dneff = (dmat[0][0] * dmat[0][0]) / dweight2 else :
dneff = 0.0
if (dneff > 3.0) :
for n1 in range(0, ndim + 1) : dvec[n1] = dvec[n1] / dmat[0][0]
for n2 in range(1, ndim + 1 ) : dmat[n1][n2] = dmat[n1][n2] / \ dmat[0][0]
if (dmat[0][0] > 0.005) : dvarw = dvarw / dmat[0][0]
else :
dvarw = 0.0
dmat[0][0] = 1.0 davew = dvec[0]
dvarw = dvarw - (davew ** 2)
if (dvarw <= 0.0) : dvarw = 10**-12
for n1 in range(1, ndim + 1) : for n2 in range(0, n1) :
dmat[n1][n2] = dmat[n2][n1]
dmat = self.matrix_inv(dmat)
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for n1 in range(0, ndim + 1) : for n2 in range(0, ndim + 1) :
dcoef[n1] = dcoef[n1] + dmat[n1][n2] * \ dvec[n2]
dpower = dpower + (dcoef[n1] * dvec[n1])
dpower = dpower - (davew ** 2)
dpowz = (dneff - 3.0) * dpower / (dvarw - dpower) / 2.0 dpower = (dneff - 1.0) * dpower / dvarw / 2.0
damp = math.sqrt(dcoef[1] * dcoef[1] + \ dcoef[2] * dcoef[2])
else :
dpowz = 0.0 dpower = 0.0 damp = 0.0
if (dneff < (10**(-9))) : dneff = 0.0
if (damp < (10**(-9))) : damp = 0.0
if (dpower < (10**(-9))) : dpower = 0.0
if (dpowz < (10**(-9))) : dpowz = 0.0
# Let's write everything out.
output[index] = [dtau, dfre, dpowz, damp, dcoef[0], dneff]
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index = index + 1
if (dpowz > dmz) : dmz = dpowz dmfre = dfre dmamp = damp dmcon = dcoef[0]
dmneff = dneff
return output
def writefile(self, wwz_output, outputFile, no_headers, max_periods) : """The write file method.
Arguments are :
wwz_output = The NumPy array of WWZ values to write outputFile = The output file pointer, not the filename no_headers = If true, will not write headers to the output max_periods = If true, will create a file with period values of maximum WWZ statistics
"""
numpy.set_printoptions(precision=5) numpy.set_printoptions(suppress=True) numpy.set_printoptions(threshold='nan')
if no_headers :
numpy.savetxt(outputFile, wwz_output, delimiter="\t", \ fmt="%10.4f")
else :
numpy.savetxt(outputFile, wwz_output, delimiter="\t", \ fmt="%10.4f", comments="#", \
header="%9s %10s %10s %10s %10s %10s" % \
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("TAU", "FREQ", "WWZ", "AMP", "COEF", "NEFF"))
def writegnu(self, wwz_output, outputFile, no_headers, \ max_periods, ntau) :
"""The write file method, adapted to work with GnuPlot.
Arguments are :
wwz_output = The NumPy array of WWZ values to write outputFile = The output file pointer, not the filename no_headers = If true, will not write headers to the output max_periods = If true, will create a file with period values of maximum WWZ statistics
ntau = The number of tau values, this is needed in order to split the wwz_output equally
To calculate ntau, use the equation below:
len(wwz_output) /
int(((freq_high - freq_low) / freq_step) + 1) """
numpy.set_printoptions(precision=5) numpy.set_printoptions(suppress=True) numpy.set_printoptions(threshold='nan')
splitArray = numpy.vsplit(wwz_output, ntau)
# check if the file is in append mode # if not, reopen it
if outputFile.mode != 'a' : outputFile.close()
outputFile = open(outputFile.name, "a")
# write headers if expected if not no_headers :
header="%9s %10s %10s %10s %10s %10s" % \
("TAU", "FREQ", "WWZ", "AMP", "COEF", "NEFF")
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outputFile.write("#" + header + "\n")
# split the array and add newlines in between tau values, # write the output
for i in range(0,ntau) :
numpy.savetxt(outputFile, splitArray[i], delimiter="\t", \ fmt="%10.4f")
if i != ntau-1 :
outputFile.write("\n")
# The WWZPAR Class Begins
class WWZPAR(object) :
"""This is for Parallel Processing only.
This works different than the WWZ class, it takes arguments directly.
It gets input as a filepointer, NOT as arrays!
Arguments :
fileName : the input filename, should be the lightcurve.
outputfileName : the output filename.
flo : the low frequency value. Float.
fhi : the high frequency value. Float.
df : the frequency step. Float.
dcon : the C Window constant. Float.
timedivisions : the The Divisions value, choose 50.0 if not sure, that is the default used by Templeton.
max_periods : set True if you want the second output file.
It outputs the tau's with maximum period values for easier estimation.
gnuplot_compatible : splits tau values by a blank line if set True, so that pm3d of gnuplot easily maps the plot.
"""
def __init__(self, fileName, outputfileName, flo, fhi, df, dcon, \
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timedivisions, max_periods, gnuplot_compatible) : """Initializing the object"""
self.inputfile = fileName
self.outputfilename1 = outputfileName
self.outputfilename2 = outputfileName.name + ".max_periods"
self.max_periods = max_periods
self.gnuplot_compatible = gnuplot_compatible
self.timedivisions = timedivisions
# This (50) is an assumption by Templeton.
# VStars leaves this optional # but keeps the default value
self.fhi = fhi self.flo = flo self.df = df
# dcon is the Window Constant "c" in Foster's equations.
self.dcon = dcon
self.fileName = fileName
self.time = [] # Input time, first column in the file
self.magnitude = [] # Input magnitude, second column in the file
self.dave = 0.0 # average self.dvar = 0.0 # variance
self.nfreq = int((self.fhi - self.flo) / self.df) + 1
self.freq = []
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self.dmat = numpy.zeros(shape=(3, 3))
def readfile(self) :
"""Read the input file"""
#read_file = open(self.inputfilename, "r") for line in self.inputfile :
if line.strip()[0] != "%" and line.strip()[0] != "#" : line_time = float(line.split()[0])
line_mag = float(line.split()[1]) self.time.append(line_time) self.magnitude.append(line_mag) self.dave = self.dave + line_mag
self.dvar = self.dvar + (line_mag ** 2)
self.inputfile.close()
if len(self.time) != len(self.magnitude) :
print "Number of Time and Magnitude input do not match. \ Please check the input file."
raise SystemExit
# Just a routine check for parameter number equality.
# This should be cleaned up a bit.
# Calculating Header Values self.numdat = len(self.time)
self.dave = self.dave / self.numdat
self.dvar = (self.dvar / self.numdat) - (self.dave ** 2)
self.dsig = math.sqrt((self.dvar * self.numdat) / (self.numdat - 1))
def roundtau(self, darg) :
"""Rounds the tau's. from G. Foster's Code."""
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dex = math.log(darg, 10) nex = int(dex)
darg = darg / math.pow(10, nex)
if darg >= 5 : darg = 5.0 elif darg >= 2 : darg = 2.0 else :
darg = 1.0
darg = darg * math.pow(10, nex) return darg
def matrix_inv(self,input_matrix) : """The Matrix Inversion Function"""
# Lines 202 - 252 Fortran
ndim = 2
dsol = numpy.zeros(shape=(3, 3))
for i in range(0, 3) : for j in range(0, 3) : dsol[i][j] = 0.0 dsol[i][i] = 1.0
for i in range(0, 3) :
if input_matrix[i][i] == 0.0 : if i == ndim :
return
for j in range(0, 3) :
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if input_matrix[j][i] != 0.0 : for k in range(0, 3) :
input_matrix[i][k] = input_matrix[i][k] + \ input_matrix[j][k]
dsol[i][j] = dsol[i][j] + dsol[j][k]
dfac = input_matrix[i][i]
for j in range(0, 3) :
input_matrix[i][j] = input_matrix[i][j] / dfac dsol[i][j] = dsol[i][j] / dfac
for j in range(0, 3) : if j != i :
dfac = input_matrix[j][i]
for k in range(0, 3) :
input_matrix[j][k] = input_matrix[j][k] - \ (input_matrix[i][k] * dfac) dsol[j][k] = dsol[j][k] - (dsol[i][k] * dfac)
return dsol
def maketau(self) :
"""The Maketau section"""
# Lines 90 - 122 Fortran
dtaulo = self.time[0] # the java translation uses 1 for this, # but that should be a bug.
dtauhi = self.time[-1]
dtspan = dtauhi - dtaulo
dtstep = self.roundtau(dtspan / self.timedivisions)
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dtaulo = dtstep * int(dtaulo / dtstep)
dtauhi = dtstep * int((dtauhi / dtstep) + 0.5)
self.tau = []
dtau = dtaulo
while dtau <= dtauhi : #print dtau
self.tau.append(dtau) dtau = dtau + dtstep
self.ntau = len(self.tau)
def makefreq(self) :
"""The Makefreq section"""
# Lines 149 - 181 Fortran # Lines 356 - 370 Java
self.freq.append(self.flo)
# These lines seem skeptical!
for i in range(1,self.nfreq+1) :
self.freq.append(self.flo + ((i - 1) * self.df))
def wwt(self, output1_par, itau1_par, itau2_par) : """The WWZ Algorithm in Parallel Mode"""
output1 = open(output1_par, "w") max_periods = self.max_periods
gnuplot_compatible = self.gnuplot_compatible
if max_periods == True :
output2_par = output1_par + ".max_periods.par"
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output2 = open(output2_par, "w")
dvec = [0,0,0] # length is 3 dcoef = [0,0,0] # length is 3
itau = 0 ifreq = 0 idat = 0
domega = 0.0 dweight2 = 0.0 dz = 0.0 dweight = 0.0
dcc = 0.0 dcw = 0.0 dss = 0.0 dsw = 0.0 dxw = 0.0 dvarw = 0.0
dtau = 0.0
dpower = 0.0 dpowz = 0.0 damp = 0.0 dneff = 0.0 davew = 0.0
dfre = 0.0
n1 = 0 n2 = 0
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dmz = 0.0 dmzfre = 0.0 dmzamp = 0.0 dmcon = 0.0 dmneff = 0.0
twopi = 2.0 * math.pi
ndim = 2
itau1 = 0 # ----> 1 or 0 ??
itau2 = self.ntau # ---> ???
ifreq1 = 1
ifreq2 = self.nfreq nstart = 1
dmat_par = numpy.zeros(shape=(3, 3))
for itau in range(itau1_par, itau2_par) : nstart = 1
dtau = self.tau[itau]
dmfre = 0.0 dmamp = 0.0 dmcon = 0.0 dmneff = 0.0
dmz = -1.0 # less than the smallest WWZ
for ifreq in range(ifreq1, ifreq2 + 1) : dfre = self.freq[ifreq]
domega = dfre * twopi
for i in range(0, ndim + 1) : dvec[i] = 0.0
for j in range(0, ndim + 1) :
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dmat_par[i][j] = 0.0
dweight2 = 0.0
for idat in range(nstart, self.numdat) :
dz = domega * (self.time[idat] - dtau)
dweight = math.exp(-1.0 * self.dcon * dz * dz)
if (dweight > 10**(-9)) : dcc = math.cos(dz) dcw = dweight * dcc dss = math.sin(dz) dsw = dweight * dss
dmat_par[0][0] = dmat_par[0][0] + dweight dweight2 = dweight2 + (dweight**2)
dmat_par[0][1] = dmat_par[0][1] + dcw dmat_par[0][2] = dmat_par[0][2] + dsw
dmat_par[1][1] = dmat_par[1][1] + (dcw * dcc) dmat_par[1][2] = dmat_par[1][2] + (dcw * dss) dmat_par[2][2] = dmat_par[2][2] + (dsw * dss)
dxw = dweight * self.magnitude[idat]
dvec[0] = dvec[0] + dxw
dvarw = dvarw + (dxw * self.magnitude[idat]) dvec[1] = dvec[1] + (dcw * self.magnitude[idat]) dvec[2] = dvec[2] + (dsw * self.magnitude[idat])
elif dz > 0.0 : break else :
nstart = idat + 1
dpower = 0.0
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damp = 0.0
for n1 in range(0, ndim + 1) : dcoef[n1] = 0.0
if (dweight2 > 0.0) :
dneff = (dmat_par[0][0] * dmat_par[0][0]) / dweight2 else :
dneff = 0.0
if (dneff > 3.0) :
for n1 in range(0, ndim + 1) :
dvec[n1] = dvec[n1] / dmat_par[0][0]
for n2 in range(1, ndim + 1 ) :
dmat_par[n1][n2] = dmat_par[n1][n2] / \ dmat_par[0][0]
if (dmat_par[0][0] > 0.0) :
dvarw = dvarw / dmat_par[0][0]
else :
dvarw = 0.0
dmat_par[0][0] = 1.0 davew = dvec[0]
dvarw = dvarw - (davew ** 2)
if (dvarw <= 0.0) : dvarw = 10**-12
for n1 in range(1, ndim + 1) : for n2 in range(0, n1) :
dmat_par[n1][n2] = dmat_par[n2][n1]
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dmat_par = self.matrix_inv(dmat_par)
for n1 in range(0, ndim + 1) : for n2 in range(0, ndim + 1) : dcoef[n1] = dcoef[n1] + \
dmat_par[n1][n2] * dvec[n2]
dpower = dpower + (dcoef[n1] * dvec[n1])
dpower = dpower - (davew ** 2)
dpowz = (dneff - 3.0) * dpower / (dvarw - dpower) / 2.0 dpower = (dneff - 1.0) * dpower / dvarw / 2.0
damp = math.sqrt(dcoef[1] * dcoef[1] + \ dcoef[2] * dcoef[2])
else :
dpowz = 0.0 dpower = 0.0 damp = 0.0
if (dneff < (10**(-9))) : dneff = 0.0
if (damp < (10**(-9))) : damp = 0.0
if (dpower < (10**(-9))) : dpower = 0.0
if (dpowz < (10**(-9))) : dpowz = 0.0
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# Let's write everything out.
output1.write("%s \t %s \t %s \t %s \t %s \t %s\n" % \ (str(dtau),str(dfre),str(dpowz),str(damp), \ str(dcoef[0]),str(dneff)))
if (dpowz > dmz) : dmz = dpowz dmfre = dfre dmamp = damp dmcon = dcoef[0]
dmneff = dneff
#
if max_periods == True :
# writes the max_periods output if specified
output2.write("%f \t %f \t %f \t %f \t %f \t %f\n" % \ (dtau, dmfre, dmz, dmamp, dmcon, dmneff))
if gnuplot_compatible == True :
# added so that gnuplot reads out of the box output1.write("\n")
# If the script runs as a standalone, below is triggered
if __name__ == '__main__' :
# Parsing the arguments
description = """
A Weighted Wavelet Z-Transformation Application for Python.
Translated by M. Emre Aydin - emre.m.aydin@gmail.com
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http://about.me/emre.aydin
Available at http://github.com/eaydin
Input arguments can be read from a file. The file descriptor prefix is '@'.
In order to read argument from a file named args.txt, the argument @args.txt should be passed.
An example for args.txt :
-f=myinputfile.txt -o=theoutputfile.output -m
--freq-step=0.001 -l=0.001
-hi=0.01 -c=0.001 -p=0
You can pass arguments from file and commandline at the same time.
If two same arguments passed by this method, the latter will be used. So if you want to override some arguments in a an argument file, specify the file first.
An example usage for our earlier @args.txt is as :
python wwz.py @args.txt -c=0.0125
The above command will use the settings in args.txt but will use c=0.0125 instead of c=0.001
Comments and blank lines are NOT allowed in argument files.
Import this script via Python to use it as a module, rather than a standalone script. (import wwz)
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"""
parser = argparse.ArgumentParser(prog='wwz.py', \
formatter_class=argparse.RawDescriptionHelpFormatter,\
fromfile_prefix_chars="@", description=description)
parser.add_argument("-f", "--file", type=argparse.FileType("r"),\
default=sys.stdin, required=True,\
help="the Input File, Raw Lightcurve")
parser.add_argument("-o", "--output", type=argparse.FileType('w'),\
default=sys.stdout, required=True,\
help="the Output File Name")
parser.add_argument("-l", "--freq-low", type=float, required=True,\
help="the Low Frequency Value")
parser.add_argument("-hi", "--freq-high", type=float, required=True,\
help="the High Frequency Value")
parser.add_argument("-d", "--freq-step", type=float, required=True,\
help="the dF value, incremental step for Frequency") parser.add_argument("-c", "--dcon", type=float, required=True,\
help="the C constant for the Window Function") parser.add_argument("-g", "--gnuplot-compatible", action="store_true",\
default=False, help="the Output file is GNUPlot \ compatible, which means the tau's will be grouped \ so that pm3d can easily map. Default value is \ 'False'.")
parser.add_argument("-m", "--max-periods", action="store_true", \ default=False, help="Creates a secondary \
output with the maximum Periods for each single \ tau. This can be drawn in 2D. The output filename \ is derived from the -o option, added 'max_periods'. \ Default value is 'False'.")
parser.add_argument("-t", "--time-divisions", type=float, default=50.0, \ help="The Time Divisions value. Templeton assumes \ this as 50. VStars from AAVSO leaves this optional \
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contrary to Templeton, yet it's default value is \ also 50.")
parser.add_argument("--time", action="store_true", default=False, \ help="Calculate the time of operation in seconds \ and print to standard output.")
parser.add_argument("--no-headers", action="store_true", default=False, \ help="Doesn't print headers to output files if set. \ Default is 'False'.")
parser.add_argument("-p", "--parallel", help="Created threads to speed \ up the process. Default value is '1', which means \ single thread. '0' means number of detected CPUs,\
can be overridden.", type=int, default=1)
args = parser.parse_args()
# Check if user asks for time calculation if args.time :
starttime = datetime.now()
# Get the process number cpu=args.parallel
if cpu != 1 : try :
import multiprocessing
except (ImportError, NotImplementedError) :
print "Multiprocessing not available, using single CPU thread."
cpu = 1
if cpu == 0 :
# detect CPU cores try :
import multiprocessing
cpu = multiprocessing.cpu_count()
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except (ImportError, NotImplementedError) :
print "Multiprocessing not available, using single CPU thread."
cpu = 1
# Multiprocessing begins if cpu != 1 :
s=WWZPAR(args.file, args.output, args.freq_low, args.freq_high, \ args.freq_step, args.dcon, args.time_divisions, \
args.max_periods, args.gnuplot_compatible)
s.readfile() s.maketau() s.makefreq()
# the list of output filenames output_par_names = []
for i in range(1,cpu+1) :
output_par_names.append('wwz.par.proc.%i' % i)
ntau_par1 = s.ntau/cpu
# the last ntau_par (turns out this is not necessary) ntau_par2 = s.ntau - (ntau_par1 * (cpu-1) )
thread_list = []
for i in range(1,cpu+1) : if i != cpu :
t = multiprocessing.Process(target=s.wwt, \
args=(output_par_names[i-1],ntau_par1*(i-1),ntau_par1*i)) else :
t = multiprocessing.Process(target=s.wwt, \
args=(output_par_names[i-1],ntau_par1*(i-1),s.ntau))
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thread_list.append(t)
for thread in thread_list : thread.start()
for thread in thread_list : thread.join()
# join the outputs and delete remaining files
if args.max_periods :
output_max_periods = open(args.output.name + ".max_periods", "w")
# Write the headers if asked if not args.no_headers :
args.output.write("#%9s %10s %10s %10s %10s %10s\n" % \ ("TAU","FREQ","WWZ","AMP","COEF","NEFF")) if args.max_periods :
output_max_periods.write("#%9s %10s %10s %10s %10s %10s\n" % \ ("TAU","FREQ","WWZ","AMP","COEF","NEFF"))
for i in range(1,cpu+1) :
read_par = open(output_par_names[i-1],"r") for line in read_par :
args.output.write(line) read_par.close()
os.remove(output_par_names[i-1])
if args.max_periods :
read_par_max = open(output_par_names[i-1] + \ ".max_periods.par","r") for line in read_par_max :
output_max_periods.write(line) read_par_max.close()
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os.remove(output_par_names[i-1] + ".max_periods.par")
# for single threadding computing if cpu == 1 :
# Run the main class and its subroutines
s=WWZ()
time_data, magnitude_data = s.readfile(args.file)
wwz_output = s.wwt(time_data, magnitude_data, args.freq_low, \ args.freq_high, args.freq_step, args.dcon, \ args.time_divisions)
if args.gnuplot_compatible :
send_ntau = len(wwz_output) / \
int(((args.freq_high - args.freq_low) / args.freq_step) + 1)
s.writegnu(wwz_output, args.output, args.no_headers, \ args.max_periods, send_ntau)
else :
s.writefile(wwz_output, args.output, \
args.no_headers, args.max_periods)
args.output.close()
if args.max_periods == True and cpu != 1 : output_max_periods.close()
# Print calculated time if args.time :
endtime = datetime.now()
print "Run Time : %s seconds" % str((endtime - starttime).seconds)
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